Reverse Engineering Partially Documented Enterprise Software: Methods, Tools, Use Cases, and Practical Recommendations

Abstract
Reverse engineering partially documented enterprise systems (such as Sparx Enterprise Architect projects, legacy ERPs, or bespoke middleware) requires a multi-faceted approach combining static and dynamic analysis, model reconstruction, and continuous documentation. This paper provides an expanded methodology, compares industry-standard tools, presents use cases and examples from real-world enterprise contexts, and offers practical recommendations. It also highlights how service providers like KeenComputer.com and IAS-Research.com can support enterprises in discovery, knowledge capture, and modernization. The study is grounded in academic research, industry best practices, and tool documentation.

1. Introduction

Enterprise applications evolve over decades, often leaving behind fragmented or outdated documentation. Reverse engineering (RE) aims to recover architecture, models, and business rules to facilitate modernization, compliance, or system integration. Sparx Enterprise Architect (EA), widely used for UML modeling, often hosts partially outdated or incomplete models. This paper explores methods for extracting actionable knowledge from such environments.

Contributions of this paper:

• A reproducible stepwise methodology for RE.
• Comparative evaluation of RE tools (binary-level, model-level, and repository-level).
• Use cases and examples from enterprise contexts.
• Guidance for research and practice.
• A roadmap for organizations leveraging external expertise.

2. Problem Statement and Challenges

Key challenges when reverse engineering enterprise systems:

• Incomplete documentation: Models and code bases diverge over time, making EA repositories partially obsolete.
• Technology heterogeneity: Mixed platforms (Java, .NET, COBOL, databases, native binaries).
• Obfuscation and packing: Security layers obscure binaries.
• Organizational memory loss: Knowledge retained only by a small subset of engineers.
• Compliance pressures: Financial, healthcare, and government systems require traceability and audit-ready documentation.

3. Recommended Methodology (Stepwise)

1. Information Gathering: Collect EA project files, repositories, configs, and database schemas. Interview stakeholders to validate goals.
2. Prescreening & Triage: Identify languages, frameworks, and third-party libraries. Detect packed/obfuscated binaries using PEiD or similar.
3. Static Analysis & Model Reconstruction: Use EA’s DB Builder to update relational models, code engineering for supported languages, and Ghidra/IDA for binaries.
4. Dynamic Analysis: Profile systems using tools like VisualVM, YourKit, or strace to trace runtime behavior.
5. Architecture Mapping: Construct dependency graphs, sequence diagrams, and context models.
6. Validation & Documentation: Compare models with observed runtime behavior. Generate documentation using Swimm or Sphinx.
7. Round-trip Engineering: Synchronize EA UML models with source code and databases to maintain model accuracy.

4. Tool Comparison Framework

To help practitioners choose the right tools, Table 1 provides a structured comparison across categories.

Table 1: Reverse Engineering Tool Comparison

5. Use Cases & Examples

Use Case 1: Banking Core Modernization

Context: A financial institution with COBOL services, Oracle DB, and EA diagrams outdated by 10 years.
Tools Used: Swimm for COBOL documentation, EFCore Power Tools for DB extraction, EA DB Builder for UML synchronization.
Outcome: Restored traceability for compliance audits, enabling migration to microservices.

Use Case 2: Healthcare ERP Migration

Context: A healthcare ERP with .NET and SQL Server, EA project partially reflecting old schema.
Tools Used: dnSpy for decompiling .NET assemblies, EFCore Power Tools for schema scaffolding, EA code engineering.
Outcome: Extracted class models, reconciled with EA, ensuring HIPAA compliance and enabling new features.

Use Case 3: Government Legacy Integration

Context: A government IT agency integrating old Java systems with new digital services.
Tools Used: CFR (Java decompiler), Ghidra for binaries, EA UML synchronization.
Outcome: Identified integration points and refactored APIs for cloud-ready services.

Use Case 4: Manufacturing Supply Chain Analytics

Context: Manufacturing ERP with mixed Java/C++ stack, fragmented EA documentation.
Tools Used: IDA Pro for binary components, EA DB Builder for schema synchronization, SonarQube for metrics.
Outcome: Unified system architecture, supporting predictive analytics deployment.

Use Case 5: E-Commerce Platform Upgrade

Context: Magento-based enterprise e-commerce platform integrating legacy plugins with modern APIs.
Tools Used: EA UML reverse engineering, PHP static analyzers, Swimm for documenting plugin code.
Outcome: Improved maintainability, reduced technical debt, and enabled migration to cloud infrastructure.

6. Evaluation Framework

Criteria to select tools:

• System type: Legacy binary vs. high-level source code.
• Budget: Commercial (IDA Pro) vs. open-source (Ghidra, Radare2).
• Integration with EA: For organizations already using EA, built-in reverse engineering is optimal.
• Documentation needs: Use Swimm and CI/CD integration for continuous documentation.
• Compliance: Choose tools with traceability features for regulated industries.

7. Documentation Recommendations

• Maintain executive summaries for stakeholders.
• Develop technical atlases: UML diagrams, ERDs, and call graphs.
• Establish living documentation pipelines with Swimm or Sphinx.
• Store outputs in a knowledge base (e.g., Confluence, Git-based wiki).
• Automate EA round-trip engineering in CI/CD pipelines.

8. Role of KeenComputer.com and IAS-Research.com

• KeenComputer.com: Provides expertise in CMS platforms (Magento, WordPress, Joomla) and connects RE outputs with digital transformation projects. Also supports cloud migration and integration with modern web stacks.
• IAS-Research.com: Delivers advanced reverse engineering support, integrating research-grade tools (Ghidra, IDA) with enterprise-ready practices. Also specializes in RAG-LLM integration for knowledge extraction from code bases.
• Combined Value: Jointly deliver scoping, execution, documentation, and migration strategies, ensuring SMEs and large enterprises alike can modernize legacy systems efficiently.

9. Ethics, Legal, and Governance

• Always confirm licensing rights before RE.[2]
• Ensure compliance with GDPR, HIPAA, or industry standards during analysis.
• Use privacy-preserving sandboxes for sensitive data.

10. Conclusion

Reverse engineering partially documented enterprise software requires combining tools, methodologies, and expertise. Use cases from banking, healthcare, government, manufacturing, and e-commerce demonstrate that RE restores system knowledge, ensures compliance, and supports modernization. Tool comparison frameworks and partner support provide enterprises with pathways to select appropriate tools and accelerate transformation.

References

[1] Apriorit Blog – Reverse Engineering Tools.
[2] Ammar, H.H. – Concerns-Based Reverse Engineering, JOIV Journal.
[3] Swimm.io – Reverse Engineering in Software Engineering Best Practices.
[4] UMLChannel – Reverse Engineer EA Project DB Schema.
[5] SparxSystems Documentation – Code Engineering and Reverse Engineering.
[6] Yurichev, D. – Reverse Engineering for Beginners.
[7] Eilam, E. – Reversing: Secrets of Reverse Engineering.
[8] Dang, B. et al. – Practical Reverse Engineering.
[9] Overcast Blog – Reverse Engineering COBOL Codebases.
[10] EFCore Power Tools Documentation.
[11] SecurityBreak.io – Book Recommendations for Malware RE.
[12] FreeComputerBooks.com – Reverse Engineering Books.
[13] O’Reilly Learning – Software Reverse Engineering Collection.

• RESEARCH METHOD
• SOFTWARE ENGINEERING
• HARDWARE SOFTWARE CODESIGN
• UML ARCHITECTURE
• RESEARCH JOURNAL
• CONSULTING ENGINEERING
• ENGINEERING and INNOVATION
• KEEN Computer Solution